At a Glance
- Tasks: Design cloud-based data architectures and provide analytics solutions for top financial institutions.
- Company: Join AWS, the leading cloud platform with a focus on innovation and collaboration.
- Benefits: Competitive salary, inclusive culture, mentorship, and opportunities for career growth.
- Other info: Dynamic environment with a focus on work/life balance and continuous learning.
- Why this job: Make a real impact in the financial services sector using cutting-edge technology.
- Qualifications: Bachelor's degree or equivalent experience in IT, analytics, or related fields.
The predicted salary is between 63000 - 103000 £ per year.
Salary: £63,000 - 103,000 per year
Requirements:
- Bachelor's degree in computer science, engineering, mathematics or equivalent, or experience in a professional field or military
- Experience in IT development or implementation/consulting in the software or Internet industries
- Experience within specific technology domain areas such as software development, cloud computing, systems engineering, infrastructure, security, networking, or data & analytics
- Experience in design, implementation, or consulting in applications and infrastructures
- Experience communicating across technical and non-technical audiences, including executive-level stakeholders or clients
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with one or more analytics visualization tools such as Excel, Tableau, QuickSight, MicroStrategy, or PowerBI
- Experience implementing cloud-based data and analytics solutions in production environments
- Knowledge of modern data architecture patterns such as data mesh, data lakehouse, or event-driven analytics
- Familiarity with common financial services data platforms and vendors such as KDB+, Bloomberg, Snowflake, and Databricks, and how they integrate with cloud-native services
Responsibilities:
- Serve as the trusted technical advisor for analytics and data strategy across a small number of the largest, most complex Global Financial Services accounts in EMEA and APJ
- Design comprehensive cloud-based data and analytics architectures tailored to the unique requirements of tier-one financial institutions, including regulatory compliance, data sovereignty, and operational resilience
- Collaborate closely with account-aligned sales teams, account managers, and broader specialist SA communities to shape and execute long-term technical strategies
- Engage at senior technical and executive levels within customer organisations, translating complex technical concepts into business-aligned recommendations
- Develop reference architectures, best practice guidance, and reusable assets that address common patterns and challenges within global financial services
- Create thought leadership content, including whitepapers, blog posts, presentations, and workshops, that demonstrates expertise in analytics, data management, and cloud modernisation for financial services
- Partner with global specialist SA peers, service teams, and product groups to influence roadmap priorities based on customer needs
- Stay current on emerging trends in data analytics, AI/ML, and financial services technology, and feed insights back into customer engagements and internal communities
Technologies:
- AI
- AWS
- AWS Glue
- Lambda
- Redshift
- Cloud
- Databricks
- Excel
- IAM
- Support
- Security
- Snowflake
- Tableau
- Web
- Architect
We are Amazon Web Services (AWS), the world's most comprehensive and broadly adopted cloud platform. Within our Global Financial Services organisation, we support a focused portfolio of strategic accounts across EMEA and APJ, working on deeply technical and strategically significant engagements. We value diverse experiences, curiosity, connection, mentorship, career growth, and work/life balance, and we offer an inclusive team culture where we solve problems that don't have off-the-shelf answers and help customers modernise analytics platforms and unlock business value from data at enterprise scale.
Specialist Analytics Solution Architect employer: AmazonWebServices
At Amazon Web Services (AWS), we are committed to fostering a culture of innovation and inclusivity, making us an exceptional employer for those in the Site Reliability Engineering Services role. Our employees benefit from extensive mentorship and career growth opportunities, alongside a strong emphasis on work-life balance, ensuring that personal well-being is valued as much as professional success. Join us in building the future of cloud computing while being part of a team that celebrates diversity and encourages collaboration.
StudySmarter Expert Advice🤫
We think this is how you could land Specialist Analytics Solution Architect
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like AmazonWebServices!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Specialist Analytics Solution Architect at AmazonWebServices.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like AmazonWebServices.
✨Apply Directly through Our Website
When you find a suitable opening like Specialist Analytics Solution Architect at AmazonWebServices, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Specialist Analytics Solution Architect
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at AmazonWebServices, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at AmazonWebServices. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at AmazonWebServices
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at AmazonWebServices!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.